On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (IJCAI, 2022)

A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. - Quanyu Dai; Haoxuan Li 001; Peng Wu 012; Zhenhua Dong; Xiao-Hua Zhou; Rui Zhang 079; Rui Zhang 003; Jie Sun 007 (KDD, 2022)

Causal Analysis Framework for Recommendation. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (CoRR, 2022)

Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random. - Peng Wu 012; Haoxuan Li 001; Yan Lyu; Xiao-Hua Zhou (CoRR, 2022)

Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. - Haoxuan Li 001; Chunyuan Zheng 001; Xiao-Hua Zhou; Peng Wu 012 (CoRR, 2022)

Multiple Robust Learning for Recommendation. - Haoxuan Li 001; Quanyu Dai; Yuru Li; Yan Lyu; Zhenhua Dong; Xiao-Hua Zhou; Peng Wu 012 (AAAI, 2023)

CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. - Jun Wang 012; Haoxuan Li 001; Chi Zhang; Dongxu Liang; Enyun Yu; Wenwu Ou; Wenjia Wang (ICDM, 2023)

TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. - Haoxuan Li 001; Yan Lyu; Chunyuan Zheng 001; Peng Wu 012 (ICLR, 2023)

StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. - Haoxuan Li 001; Chunyuan Zheng 001; Peng Wu 012 (ICLR, 2023)

Propensity Matters: Measuring and Enhancing Balancing for Recommendation. - Haoxuan Li 001; Yanghao Xiao; Chunyuan Zheng 001; Peng Wu 012; Peng Cui 001 (ICML, 2023)

Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. - Haoxuan Li 001; Chunyuan Zheng 001; Yixiao Cao; Zhi Geng; Yue Liu; Peng Wu 012 (ICML, 2023)

Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. - Haoxuan Li 001; Chunyuan Zheng 001; Peng Wu 012; Kun Kuang; Yue Liu; Peng Cui 001 (KDD, 2023)

Pareto Invariant Representation Learning for Multimedia Recommendation. - Shanshan Huang 004; Haoxuan Li 001; Qingsong Li; Chunyuan Zheng 001; Li Liu 001 (ACM Multimedia, 2023)

Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. - Jinqiu Jin; Haoxuan Li 001; Fuli Feng; Sihao Ding 003; Peng Wu 012; Xiangnan He 001 (NeurIPS, 2023)

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. - Haoxuan Li 001; Kunhan Wu; Chunyuan Zheng 001; Yanghao Xiao; Hao Wang 049; Zhi Geng; Fuli Feng; Xiangnan He 001; Peng Wu 012 (NeurIPS, 2023)

Optimal Transport for Treatment Effect Estimation. - Hao Wang 049; Jiajun Fan; Zhichao Chen 001; Haoxuan Li 001; Weiming Liu 005; Tianqiao Liu; Quanyu Dai; Yichao Wang 002; Zhenhua Dong; Ruiming Tang (NeurIPS, 2023)

ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. - Haoxuan Li 001; Taojun Hu; Zetong Xiong; Chunyuan Zheng 001; Fuli Feng; Xiangnan He 001; Xiao-Hua Zhou (RecSys, 2023)

Causal Recommendation: Progresses and Future Directions. - Wenjie Wang 007; Yang Zhang 072; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (SIGIR, 2023)

Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. - Haoxuan Li 001; Yanghao Xiao; Chunyuan Zheng 001; Peng Wu 012 (WWW, 2023)

ConvFormer: Revisiting Transformer for Sequential User Modeling. - Hao Wang 049; Jianxun Lian; Mingqi Wu; Haoxuan Li 001; Jiajun Fan; Wanyue Xu; Chaozhuo Li; Xing Xie 001 (CoRR, 2023)

Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. - Anpeng Wu; Haoxuan Li 001; Kun Kuang; Keli Zhang; Fei Wu 001 (CoRR, 2023)

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Xiaoqing Yang; Xuan Qin; Peng Zhen 001; Jiecheng Guo; Fei Wu 001; Kun Kuang (AAAI, 2024)

Uncovering the Propensity Identification Problem in Debiased Recommendations. - Honglei Zhang; Shuyi Wang; Haoxuan Li 001; Chunyuan Zheng 001; Xu Chen 017; Li Liu 001; Shanshan Luo; Peng Wu 012 (ICDE, 2024)

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. - Haoxuan Li 001; Chunyuan Zheng 001; Sihao Ding 003; Peng Wu 012; Zhi Geng; Fuli Feng; Xiangnan He 001 (ICLR, 2024)

Debiased Collaborative Filtering with Kernel-Based Causal Balancing. - Haoxuan Li 001; Chunyuan Zheng 001; Yanghao Xiao; Peng Wu 012; Zhi Geng; Xu Chen 017; Peng Cui 001 (ICLR, 2024)

MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. - Min Zhang 005; Haoxuan Li 001; Fei Wu 001; Kun Kuang (ICLR, 2024)

On the Maximal Local Disparity of Fairness-Aware Classifiers. - Jinqiu Jin; Haoxuan Li 001; Fuli Feng (ICML, 2024)

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. - Baohong Li; Haoxuan Li 001; Anpeng Wu; Minqin Zhu; Shiyuan Peng; Qingyu Cao; Kun Kuang (ICML, 2024)

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. - Baohong Li; Haoxuan Li 001; Ruoxuan Xiong; Anpeng Wu; Fei Wu 001; Kun Kuang (ICML, 2024)

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering. - Haoxuan Li 001; Chunyuan Zheng 001; Shuyi Wang; Kunhan Wu; Eric Hao Wang; Peng Wu 012; Zhi Geng; Xu Chen 017; Xiao-Hua Zhou (ICML, 2024)

Learning Causal Relations from Subsampled Time Series with Two Time-Slices. - Anpeng Wu; Haoxuan Li 001; Kun Kuang; Keli Zhang; Fei Wu 001 (ICML, 2024)

Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. - Wenjing Yang 002; Haotian Wang 001; Haoxuan Li 001; Hao Zou 001; Ruochun Jin; Kun Kuang; Peng Cui 001 (KDD, 2024)

Debiased Recommendation with Noisy Feedback. - Haoxuan Li 001; Chunyuan Zheng 001; Wenjie Wang 007; Hao Wang 049; Fuli Feng; Xiao-Hua Zhou (KDD, 2024)

Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective. - Zhichao Chen 001; Haoxuan Li 001; Fangyikang Wang; Odin Zhang; Hu Xu; Xiaoyu Jiang; Zhihuan Song; Hao Wang 049 (NeurIPS, 2024)

Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization. - Zhikang Chen; Min Zhang 005; Sen Cui; Haoxuan Li 001; Gang Niu 001; Mingming Gong; Changshui Zhang; Kun Zhang 001 (NeurIPS, 2024)

Towards Understanding Extrapolation: a Causal Lens. - Lingjing Kong; Guangyi Chen 002; Petar Stojanov; Haoxuan Li 001; Eric P. Xing; Kun Zhang 001 (NeurIPS, 2024)

TransFR: Transferable Federated Recommendation with Pre-trained Language Models. - Honglei Zhang; He Liu; Haoxuan Li 001; Yidong Li (CoRR, 2024)

FreDF: Learning to Forecast in Frequency Domain. - Hao Wang 049; Licheng Pan; Zhichao Chen 001; Degui Yang; Sen Zhang 006; Yifei Yang; Xinggao Liu; Haoxuan Li 001; Dacheng Tao (CoRR, 2024)

Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. - Yingrong Wang; Anpeng Wu; Haoxuan Li 001; Weiming Liu 005; Qiaowei Miao; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games. - Anjie Liu; Jianhong Wang; Haoxuan Li 001; Xu Chen 017; Jun Wang 012; Samuel Kaski; Mengyue Yang (CoRR, 2024)

Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation. - Honglei Zhang; Haoxuan Li 001; Jundong Chen 003; Sen Cui; Kunda Yan; Abudukelimu Wuerkaixi; Xin Zhou 008; Zhiqi Shen 001; Yidong Li (CoRR, 2024)

Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow. - Zhichao Chen 001; Haoxuan Li 001; Fangyikang Wang; Odin Zhang; Hu Xu; Xiaoyu Jiang; Zhihuan Song; Eric H. Wang (CoRR, 2024)

Proximity Matters: Local Proximity Preserved Balancing for Treatment Effect Estimation. - Hao Wang 049; Zhichao Chen 001; Yuan Shen; Jiajun Fan; Zhaoran Liu; Degui Yang; Xinggao Liu; Haoxuan Li 001 (CoRR, 2024)

Causal Inference with Complex Treatments: A Survey. - Yingrong Wang; Haoxuan Li 001; Minqin Zhu; Anpeng Wu; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. - Hang Pan 006; Shuxian Bi; Wenjie Wang 007; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

FSMLP: Modelling Channel Dependencies With Simplex Theory Based Multi-Layer Perceptions In Frequency Domain. - Zhengnan Li; Haoxuan Li 001; Hao Wang 049; Jun Fang; Duoyin Li; Yunxiao Qin (CoRR, 2024)

HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units. - Guorui Liao; Chunyuan Zheng 001; Li Cheng 001; Haoyu Xie; Shanshan Huang 004; Jun Liao 001; Haoxuan Li 001; Li Liu 001 (AAAI, 2025)

Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction. - Shanshan Huang 004; Haoxuan Li 001; Chunyuan Zheng 001; Mingyuan Ge; Wei Gao; Lei Wang 197; Li Liu 001 (CVPR, 2025)

Visual Representation Learning through Causal Intervention for Controllable Image Editing. - Shanshan Huang 004; Haoxuan Li 001; Chunyuan Zheng 001; Lei Wang 197; Guorui Liao; Zhili Gong; Huayi Yang; Li Liu 001 (CVPR, 2025)

Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. - Haotian Wang 001; Haoxuan Li 001; Hao Zou 001; Haoang Chi; Long Lan; Wanrong Huang; Wenjing Yang 002 (ICLR, 2025)

FreDF: Learning to Forecast in the Frequency Domain. - Hao Wang 049; Lichen Pan; Yuan Shen; Zhichao Chen 001; Degui Yang; Yifei Yang; Sen Zhang 006; Xinggao Liu; Haoxuan Li 001; Dacheng Tao (ICLR, 2025)

Optimal Transport for Time Series Imputation. - Hao Wang 049; Zhengnan Li; Haoxuan Li 001; Xu Chen 017; Mingming Gong; BinChen; Zhichao Chen 001 (ICLR, 2025)

Classifying Treatment Responders: Bounds and Algorithms. - Anpeng Wu; Haoxuan Li 001; Chunyuan Zheng 001; Kun Kuang; Kun Zhang 001 (KDD (1), 2025)

A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding. - Chuan Zhou 013; Yaxuan Li 002; Chunyuan Zheng 001; Haiteng Zhang; Min Zhang 005; Haoxuan Li 001; Mingming Gong (KDD (1), 2025)

CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds. - Lei Wang 198; Jianxun Lian; Yi Huang; Yanqi Dai; Haoxuan Li 001; Xu Chen 017; Xing Xie 001; Ji-Rong Wen (NAACL (Long Papers), 2025)

Adaptive Structure Learning with Partial Parameter Sharing for Post-Click Conversion Rate Prediction. - Chunyuan Zheng 001; Hang Pan 006; Yang Zhang 072; Haoxuan Li 001 (SIGIR, 2025)

CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding. - Huayi Yang; Chunyuan Zheng 001; Guorui Liao; Shanshan Huang 004; Jun Liao 001; Zhili Gong; Haoxuan Li 001; Li Liu 001 (WWW, 2025)

Learning double balancing representation for heterogeneous dose-response curve estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Fei Wu 001; Kun Kuang (Neural Networks, 2025)

Entire Space Counterfactual Learning for Reliable Content Recommendations. - Hao Wang 049; Zhichao Chen 001; Zhaoran Liu; Haozhe Li; Degui Yang; Xinggao Liu; Haoxuan Li 001 (IEEE Trans. Inf. Forensics Secur., 2025)

Learning Counterfactual Outcomes Under Rank Preservation. - Peng Wu 012; Haoxuan Li 001; Chunyuan Zheng 001; Yan Zeng 002; Jiawei Chen; Yang Liu 018; Ruocheng Guo; Kun Zhang 001 (CoRR, 2025)

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting. - Licheng Pan; Zhichao Chen 001; Haoxuan Li 001; Guangyi Liu; Zhijian Xu; Zhaoran Liu; Hao Wang 049; Ying Wei (CoRR, 2025)

Learning without Isolation: Pathway Protection for Continual Learning. - Zhikang Chen; Abudukelimu Wuerkaixi; Sen Cui; Haoxuan Li 001; Ding Li; Jingfeng Zhang; Bo Han 003; Gang Niu 001; Houfang Liu; Yi Yang 039; Sifan Yang; Changshui Zhang; et al. (CoRR, 2025)

Pruning Spurious Subgraphs for Graph Out-of-Distribtuion Generalization. - Tianjun Yao; Haoxuan Li 001; Yongqiang Chen 002; Tongliang Liu; Le Song; Eric P. Xing; Zhiqiang Shen (CoRR, 2025)

Large Language Models are Demonstration Pre-Selectors for Themselves. - Jiarui Jin; Yuwei Wu; Haoxuan Li 001; Xiaoting He; Weinan Zhang 001; Yiming Yang; Yong Yu 001; Jun Wang 012; Mengyue Yang (CoRR, 2025)

Beyond Personalization: Federated Recommendation with Calibration via Low-rank Decomposition. - Jundong Chen 003; Honglei Zhang; Haoxuan Li 001; Chunxu Zhang; Zhiwei Li 007; Yidong Li (CoRR, 2025)

Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering. - Tianjun Yao; Haoxuan Li 001; Zhiqiang Shen; Pan Li; Tongliang Liu; Kun Zhang 001 (CoRR, 2025)

Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning. - Xiangning Yu 001; Zhuohan Wang; Linyi Yang; Haoxuan Li 001; Anjie Liu; Xiao Xue 001; Jun Wang 012; Mengyue Yang (CoRR, 2025)